Support and sales bots grounded in your docs, integrated with your CRM and helpdesk, and handed off to a human the moment confidence drops.
Not a menu of buzzwords — the concrete things our team delivers on every ai chatbots engagement.
RAG on your help centre, product docs, and past tickets — with citations the user can click.
Intercom, Zendesk, Freshdesk, or custom — we detect confusion and route to a human with full context.
Creates tickets, updates deals, and reads customer context so answers are personal, not generic.
Streaming responses, typing indicators, and sub-second first-token times. Chat should feel like chat.
Web widget, WhatsApp, Slack, and in-app — one brain, many surfaces, shared memory across them.
Topic guardrails, eval dashboards, and a review queue for edge cases so the bot gets better each week.
No discovery phase that never ends. Each step has a deliverable, a date, and a demo.
We index your docs and past tickets, then map the top 20 intents by volume and pain.
A working bot in two weeks, evaluated against a golden set drawn from your actual conversations.
CRM, helpdesk, and channel integrations. Human handoff rules tuned on your support team's patterns.
Weekly eval reviews, content gap reports, and prompt tuning for the first 60 days post-launch.
Opinionated defaults — not a buzzword bingo card. We swap pieces when your product calls for it.
A chatbot answers a question and stops. An agent takes an instruction, plans steps, calls tools across your systems, checks its own work and either completes the task or escalates it. Chatbots deflect tickets; agents remove recurring operational work. Most support problems are genuinely chatbot-shaped, and reaching for an agent when a grounded bot would do adds risk and cost for no gain.
Ground every answer in retrieved documentation, cite the source so the user can verify, and give the bot an explicit refusal path when retrieval confidence is low. "I could not find that — here is a human" is a correct answer, and a bot that never says it is a bot that invents. We monitor refusal rate as a health metric: near-zero usually means it is guessing.
Keep the knowledge base as the single source of truth rather than baking answers into prompts. When your docs change, the bot should change with them without a redeploy.
On a typical rollout, 40-70% of top-volume intents within about six weeks — and the honest framing is that the tail is where it stops. The first ten intents cover most of your ticket volume and automate well; the long tail of unusual, emotional or account-specific requests should go to a human, and trying to force those through the bot is how satisfaction scores fall.
Measure deflection alongside escalation quality. A bot that deflects 80% while frustrating the people it fails is worse commercially than one that deflects 50% and hands off cleanly with full conversation context attached.
A grounded support bot over existing documentation with human handoff runs $20k-$60k over 4-8 weeks. Multi-channel deployment across web, WhatsApp and your helpdesk adds to that. Running cost is usually $0.02-$0.15 per conversation. Budget an ongoing operate fee too: content gaps need closing and prompts need tuning as your product changes, and a bot nobody maintains degrades quietly.
A 30-minute call. We'll talk scope, timelines, and what a realistic first release looks like. NDA signed before we start.